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Proceedings Paper

Quantitative analysis of suspended sediment in the Yangtze River estuary from MODIS images
Author(s): Runyuan Kuang; Yunxuan Zhou; Xing Li; Fang Shen
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Paper Abstract

Spatial and temporal distributions of suspended sediment concentration (SSC) are greatly important for analyzing the deposition and erosion variety of estuaries and evaluating the fluxes from river to sea. A model based on data in situ measurements for estimating concentration of the suspended sediment with MODIS band 2 images are developed by taking Yangtze River estuary as an experimental site in this study. Numerous field spectral measurements are carried out in the Yangtze River estuary, and SSC are obtained concurrently. By analyzing the remote sensing reflectance (Rrs) and SSC, we observed that Rrs increases with SSC and their correlation coefficient is beyond 0.8 at near-infrared wavelengths (750-900nm). A linear relationship was established between SSC and Rrs at 858.5nm wavelength (the middle point of 841-876nm wavelength). Compared to MODIS band 15, 16, 17 (resolution of 1km) data, the MODIS band 2 (resolution of 250m) data is suitable to detect the horizontal distribution of suspended sediment in narrow estuaries because of relatively high spatial resolution. The linear function is applied to corrected MODIS Terra band 2 data. As a result, the horizontal distribution of SSC is retrieved in the Yangtze River estuary. This study demonstrates MODIS band 2 (250m) data provides data well suited for the study of suspended sediment in dynamic estuarine waters.

Paper Details

Date Published: 29 December 2008
PDF: 12 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728553 (29 December 2008); doi: 10.1117/12.815925
Show Author Affiliations
Runyuan Kuang, East China Normal Univ. (China)
Yunxuan Zhou, East China Normal Univ. (China)
Xing Li, East China Normal Univ. (China)
Fang Shen, East China Normal Univ. (China)

Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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